Objective: This paper proposes a new methodology that focuses on the effects of cold and harsh environments on the reliability of human performance. Background: As maritime operations move into Arctic and Antarctic environments, decision makers must be able to recognize how cold weather affects human performance and subsequently adjusts management and operational tools and strategies. Method: In the present work, a revised version of the Human Error Assessment and Reduction Technique (HEART) methodology has been developed to assess the effects of cold on the likelihood of human error in offshore oil and gas facilities. This methodology has been applied to post-maintenance tasks of offshore oil and gas facility pumps to investigate how management, operational, and equipment issues must be considered in risk analysis and prediction of human error in cold environments. Results: This paper provides a proof of concept indicating that the risk associated with operations in cold environments is greater than the risk associated with the same operations performed in temperate climates. It also develops guidelines regarding how this risk can be assessed. The results illustrate that in post-maintenance procedures of a pump, the risk value related to the effect of cold and harsh environments on operator cognitive performance is twice as high as the risk value when performed in normal conditions. Conclusion: The present work demonstrates significant differences between human error probabilities (HEPs) and associated risks in normal conditions as opposed to cold and harsh environments. This study also highlights that the cognitive performance of the human operator is the most important factor affected by the cold and harsh conditions. Application: The methodology developed in this paper can be used for reevaluating the HEPs for particular scenarios that occur in harsh environments since these HEPs may not be comparable to similar scenarios in normal conditions.
- cold regions
- human error
- risk analysis
- offshore oil and gas industry